Description:
- We know the map and the vector range reading from sensors of the robot, but we dont know where is the robot
- State space are continuous, so we cannot store the Markov model of all state, use particle filtering instead
SLAM
- Simultaneous Localization and Mapping
- We do not know the map or our location
- State consists of position AND map!
- Main techniques: Kalman filtering (Gaussian HMMs) and particle methods